Bar Plot of cook's distance to detect observations that strongly influence fitted values of the model.
An object of class
ols_plot_cooksd_bar returns a list containing the
a tibble with observation number and
cooks distance that exceed
threshold for classifying an observation as an outlier
Cook's distance was introduced by American statistician R Dennis Cook in 1977. It is used to identify influential data points. It depends on both the residual and leverage i.e it takes it account both the x value and y value of the observation.
Steps to compute Cook's distance:
Delete observations one at a time.
Refit the regression model on remaining \(n - 1\) observations
examine how much all of the fitted values change when the ith observation is deleted.
A data point having a large cook's d indicates that the data point strongly influences the fitted values.
ols_cooksd_barplot() has been deprecated. Instead use
model <- lm(mpg ~ disp + hp + wt, data = mtcars) ols_plot_cooksd_bar(model)